The focus of this week's module was the compilation of a Minimum Essential Data Set (MEDS) to support a standards-based geospatial model for GIS systems as developed by the Department of Homeland Security in the interest of prevention and protection of areas during a time of crisis. Having a standards-based geospatial model founded on a MEDS provides a uniform basis for any community or organization before and during a time of crisis, whether security- or hazard-related. The uniformity of the system ensures that at the time of crisis, the system will be available and useful to anyone involved with crisis planning or recovery. MEDS have already been created for large metropolitan areas through the cooperation of local, state, and federal government agencies.
Data for MEDS are compiled from several different internet sources; shapefiles, rasters, tables, and geodatabases are included. Layers to be included in MEDS are: orthoimagery, elevation, hydrography, transportation, boundaries, structures, land cover, and geographic names. Data must be in North America Datum of 1983 to meet MEDS specifications.
The task for this particular exercise was to identify and put together an essential dataset in preparation for the homeland security crisis of the Boston Marathon bombing. All of the necessary data for this module was downloaded from National Map Viewer and provided. After organizing the map document with a default geodatabase and stipulating the data frame's units (meters), group layers were created to organize the required MEDS layers. Each created group layer was populated with the applicable data layers. The Boston Metropolitan Statistical Area (BMSA) layers were added to the Boundaries group layer. (BMSA includes Boston, Brookline, Cambridge, Chelsea, Everett, Quincy, Revere, Somerville, and Winthrop along with a 10-mile buffer around the outer extent.) The transportation group layer was populated with three road layers (local, primary, and secondary) which were created by using Joins and Relates to join the attributes from the CFCC table to the BMSA Roads layer and then selecting by atttributes to create the three aforementioned layers. The selections were exported data (matching the coordinate system of the receiving geodatabase) and then added to the map as layers which were then adjusted for symbology and labels. Adjustments were made to the Scale Range for each transportation layer as well as the transportation labels so that clarity would reign supreme with any changes in scale.
The Hydrography group layer was populated with three feature classes that had been provided, and Orthoimagery and Elevation group layers were populated with their respective raster datasets. Working with the Landcover raster was quite a lot of fun. After using Extract by Mask to limit the area covered by the raster to only that of the BMSA, the symbology was altered using more meaningful colors imported with a color map created from the National Land Cover Database 2006 Legend. Those colors portray the types of landcover much more adequately than the random colors. Labels for the landcovers were also changed to match the color map labels.
In order to add geographic names from the Geographic Names Information System data file, the text file format was first changed from CSVDelimited to Delimited(|) format to create columns of information. The x,y coordinates of the table were then used as input to create a feature class. After saving the output to the geodatabase, the layer was added to Geographic Names group layer and then projected to the State Plane system (the re-projected layer was also added to the Geographic Names group layer). From this re-projected layer, only the features that were entirely within the 6 counties of the BMSA were selected using Select by Attributes and then Select by Location. This final selection of geographic names was exported as data, added to the map, and moved into the Geographic Names group layer as well before removing the other layer.
The creation of these seven group layers was essentially the staging portion of the geospatial model to follow. In order to make the layers accessible to others who might need to use them, each group layer was saved as a layer file. With the preparation part complete, the next step is to protect ~ the focus of next week's module.
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